The Relation of Gas Seepage and Coal Body Damage Under the True Three Dimension Stress

AbstractThe law of gas flow is the basis of coal and gas outburst prevention and gas drainage rate increase. Thus the relation of gas seepage and coal body damage under the true three dimension stress is studied. The research results show that when volume stress is not change with the change of pore pressure the permeability of coal body change with the parabolic law. The relation of damage and permeability of coal body is established. It can be known that during load of coal body the greater the damage occur, the more the permeability of coal body after unload decrease than primary permeability of coal body

The significance of machine learning in neonatal screening for inherited metabolic diseases

BackgroundNeonatal screening for inherited metabolic diseases (IMDs) has been revolutionized by tandem mass spectrometry (MS/MS). This study aimed to enhance neonatal screening for IMDs using machine learning (ML) techniques.MethodsThe study involved the analysis of a comprehensive dataset comprising 309,102 neonatal screening records collected in the Ningbo region, China. An advanced ML system model, encompassing nine distinct algorithms, was employed for the purpose of predicting the presence of 31 different IMDs. The model was compared with traditional cutoff schemes to assess its diagnostic efficacy. Additionally, 180 suspected positive cases underwent further evaluation.ResultsThe ML system exhibited a significantly reduced positive rate, from 1.17% to 0.33%, compared to cutoff schemes in the initial screening, minimizing unnecessary recalls and associated stress. In suspected positive cases, the ML system identified 142 true positives with high sensitivity (93.42%) and improved specificity (78.57%) compared to the cutoff scheme. While false negatives emerged, particularly in heterozygous carriers, our study revealed the potential of the ML system to detect asymptomatic cases.ConclusionThis research provides valuable insights into the potential of ML in pediatric medicine for IMD diagnosis through neonatal screening, emphasizing the need for accurate carrier detection and further research in this domain

Fully Automated Deep Learning-enabled Detection for Hepatic Steatosis on Computed Tomography: A Multicenter International Validation Study

Despite high global prevalence of hepatic steatosis, no automated diagnostics demonstrated generalizability in detecting steatosis on multiple international datasets. Traditionally, hepatic steatosis detection relies on clinicians selecting the region of interest (ROI) on computed tomography (CT) to measure liver attenuation. ROI selection demands time and expertise, and therefore is not routinely performed in populations. To automate the process, we validated an existing artificial intelligence (AI) system for 3D liver segmentation and used it to purpose a novel method: AI-ROI, which could automatically select the ROI for attenuation measurements. AI segmentation and AI-ROI method were evaluated on 1,014 non-contrast enhanced chest CT images from eight international datasets: LIDC-IDRI, NSCLC-Lung1, RIDER, VESSEL12, RICORD-1A, RICORD-1B, COVID-19-Italy, and COVID-19-China. AI segmentation achieved a mean dice coefficient of 0.957. Attenuations measured by AI-ROI showed no significant differences (p = 0.545) and a reduction of 71% time compared to expert measurements. The area under the curve (AUC) of the steatosis classification of AI-ROI is 0.921 (95% CI: 0.883 - 0.959). If performed as a routine screening method, our AI protocol could potentially allow early non-invasive, non-pharmacological preventative interventions for hepatic steatosis. 1,014 expert-annotated liver segmentations of patients with hepatic steatosis annotations can be downloaded here: https://drive.google.com/drive/folders/1-g_zJeAaZXYXGqL1OeF6pUjr6KB0igJX

Reliability and validity of the Chinese version of the Walsh Family Resilience Questionnaire among community-dwelling disabled elderly individuals (WFRQ-CE)

ObjectiveTo test the reliability and validity of the Chinese version of the Walsh Family Resilience Questionnaire among community-dwelling disabled elderly individuals (WFRQ-CE).MethodsConvenience sampling was used to select 566 dyads of disabled elderly individuals and their caregivers. The Walsh Family Resilience Questionnaire Chinese Version (WFRQ-C) was tested among elderly individuals. The Family Care Capacity Scale for Elderly Patients (FCCSE) was used as a concurrent validation tool for the caregivers, and the Psychological Resilience Scale (CD-RISC-10), and the Social Support Assessment (SSRS-10) were used as concurrent validation tools for both the elderly individuals and the caregivers.ResultsExploratory factor analysis (EFA) revealed four common factors–“Family belief,” “Organization and problem solving,” “Family communication,” and “Utilization of external resources”–with a cumulative variance contribution rate of 56.94%. Confirmatory factor analysis (CFA) yielded the following fit indices: chi-square/freedom degree (χ2/df) = 2.007, Tucker Lewis index (TLI) = 0.900, incremental fit index (IFI) = 0.917, comparative fit index (CFI) = 0.916, parsimony goodness-of-fit index (PGFI) = 0.681, and root-mean-square error of approximation (RMSEA) = 0.060. The concurrent scales were significantly correlated with the WFRQ-C total score and the scores for each factor (r values between 0.23 and 0.60, P < 0.01). The Cronbach’s alpha coefficient was 0.93 for the WFRQ-CE and 0.87, 0.83, 0.89, and 0.65 for the four factors; the retest reliability was 0.96 for the total scale and 0.95, 0.92, 0.92, and 0.95 for the four factors; the split-half reliability was 0.85 for the total scale, and 0.81, 0.78, 0.79, and 0.68 for the four factors.ConclusionThe WFRQ-CE has good reliability and validity among community-dwelling disabled elderly individuals and can be used to evaluate the level of family resilience

Proteome changes of lungs artificially infected with H-PRRSV and N-PRRSV by two-dimensional fluorescence difference gel electrophoresis

<p>Abstract</p> <p>Background</p> <p>Porcine reproductive and respiratory syndrome with PRRS virus (PRRSV) infection, which causes significant economic losses annually, is one of the most economically important diseases affecting swine industry worldwide. In 2006 and 2007, a large-scale outbreak of highly pathogenic porcine reproductive and respiratory syndrome (PRRS) happened in China and Vietnam. However little data is available on global host response to PRRSV infection at the protein level, and similar approaches looking at mRNA is problematic since mRNA levels do not necessarily predict protein levels. In order to improve the knowledge of host response and viral pathogenesis of highly virulent Chinese-type PRRSV (H-PRRSV) and Non-high-pathogenic North American-type PRRSV strains (N-PRRSV), we analyzed the protein expression changes of H-PRRSV and N-PRRSV infected lungs compared with those of uninfected negative control, and identified a series of proteins related to host response and viral pathogenesis.</p> <p>Results</p> <p>According to differential proteomes of porcine lungs infected with H-PRRSV, N-PRRSV and uninfected negative control at different time points using two-dimensional fluorescence difference gel electrophoresis (2D-DIGE) and mass spectrometry identification, 45 differentially expressed proteins (DEPs) were identified. These proteins were mostly related to cytoskeleton, stress response and oxidation reduction or metabolism. In the protein interaction network constructed based on DEPs from lungs infected with H-PRRSV, HSPA8, ARHGAP29 and NDUFS1 belonged to the most central proteins, whereas DDAH2, HSPB1 and FLNA corresponded to the most central proteins in those of N-PRRSV infected.</p> <p>Conclusions</p> <p>Our study is the first attempt to provide the complex picture of pulmonary protein expression during H-PRRSV and N-PRRSV infection under the in vivo environment using 2D-DIGE technology and bioinformatics tools, provides large scale valuable information for better understanding host proteins-virus interactions of these two PRRSV strains.</p

Ubiquitin Ligases RGLG1 and RGLG5 Regulate Abscisic Acid Signaling by Controlling the Turnover of Phosphatase PP2CA

[EN] Abscisic acid (ABA) is an essential hormone for plant development and stress responses. ABA signaling is suppressed by clade A PP2C phosphatases, which function as key repressors of this pathway through inhibiting ABA-activated SnRK2s (SNF1-related protein kinases). Upon ABA perception, the PYR/PYL/RCAR ABA receptors bind to PP2Cs with high affinity and biochemically inhibit their activity. While thismechanismhas been extensively studied, how PP2Cs are regulated at the protein level is only starting to be explored. Arabidopsis thaliana RING DOMAIN LIGASE5 (RGLG5) belongs to a five-member E3 ubiquitin ligase family whose target proteins remain unknown. We report that RGLG5, together with RGLG1, releases the PP2C blockade of ABA signaling by mediating PP2CA protein degradation. ABA promotes the interaction of PP2CA with both E3 ligases, which mediate ubiquitination of PP2CA and are required for ABA-dependent PP2CA turnover. Downregulation of RGLG1 and RGLG5 stabilizes endogenous PP2CA and diminishes ABA-mediated responses. Moreover, the reduced response to ABA in germination assays is suppressed in the rglg1 amiR (artificial microRNA)-rglg5 pp2ca-1 triple mutant, supporting a functional link among these loci. Overall, our data indicate that RGLG1 and RGLG5 are important modulators of ABA signaling, and they unveil amechanismfor activation of the ABA pathway by controlling PP2C half-life.We thank Andreas Bachmair for the rglg1 mutant, Sean R. Cutler for the pyr1 pyl1 pyl2 pyl4 seeds, Dapeng Zhang for the transgenic material harboring ABI2, Hongwei Guo and Jianmin Zhou for the pCAMBIA1300-Nluc and pCAMBIA1300-Cluc vectors, and John Olson for assistance in English editing. Work in C.A.'s laboratory was supported by grants from the National Key Basic Science "973" Program (Grant 2012CB114006), the National Natural Science Foundation (Grants 31272023, 31170231, and 90817001) of the Chinese government, and by the State Key Laboratory of Protein and Plant Gene Research, Peking University. Work in P.L.R.'s laboratory was supported by Ministerio de Ciencia e Innovacion, Fondo Europeo de Desarrollo Regional, and Consejo Superior de Investigaciones Cientificas (Grant BIO2014-52537-R).Wu, Q.; Zhang, X.; Peirats-Llobet, M.; Belda Palazón, B.; Wang, X.; Cui, S.; Yu, X.... (2016). Ubiquitin Ligases RGLG1 and RGLG5 Regulate Abscisic Acid Signaling by Controlling the Turnover of Phosphatase PP2CA. Plant Cell. 28(9):2178-2196. https://doi.org/10.1105/tpc.16.003642178219628

Cyclization reaction of amines with dialkyl carbonates to yield 1,3-oxazinan-2-ones

A number of six-membered cyclic carbamates (oxazinanones) were synthesized from the reaction of a primary amine or hydrazine with a dicarbonate derivative of 1,3-diols in a one-pot reaction, in good yield, short time span, and in the absence of a solvent. The reaction proceeds in two steps: an intermolecular reaction to give a linear intermediate and an intramolecular cyclization to yield the cyclic carbamate. This is the first example of a carbonate reacting selectively and sequentially, firstly at the carbonyl center to form a linear carbamate and then as a leaving group to yield a cyclic carbamate

Arabidopsis Hormone Database: a comprehensive genetic and phenotypic information database for plant hormone research in Arabidopsis

Plant hormones are small organic molecules that influence almost every aspect of plant growth and development. Genetic and molecular studies have revealed a large number of genes that are involved in responses to numerous plant hormones, including auxin, gibberellin, cytokinin, abscisic acid, ethylene, jasmonic acid, salicylic acid, and brassinosteroid. Here, we develop an Arabidopsis hormone database, which aims to provide a systematic and comprehensive view of genes participating in plant hormonal regulation, as well as morphological phenotypes controlled by plant hormones. Based on data from mutant studies, transgenic analysis and gene ontology (GO) annotation, we have identified a total of 1026 genes in the Arabidopsis genome that participate in plant hormone functions. Meanwhile, a phenotype ontology is developed to precisely describe myriad hormone-regulated morphological processes with standardized vocabularies. A web interface (http://ahd.cbi.pku.edu.cn) would allow users to quickly get access to information about these hormone-related genes, including sequences, functional category, mutant information, phenotypic description, microarray data and linked publications. Several applications of this database in studying plant hormonal regulation and hormone cross-talk will be presented and discussed

Whole exome sequencing identifies frequent somatic mutations in cell-cell adhesion genes in chinese patients with lung squamous cell carcinoma

Lung squamous cell carcinoma (SQCC) accounts for about 30% of all lung cancer cases. Understanding of mutational landscape for this subtype of lung cancer in Chinese patients is currently limited. We performed whole exome sequencing in samples from 100 patients with lung SQCCs to search for somatic mutations and the subsequent target capture sequencing in another 98 samples for validation. We identified 20 significantly mutated genes, including TP53, CDH10, NFE2L2 and PTEN. Pathways with frequently mutated genes included those of cell-cell adhesion/Wnt/Hippo in 76%, oxidative stress response in 21%, and phosphatidylinositol-3-OH kinase in 36% of the tested tumor samples. Mutations of Chromatin regulatory factor genes were identified at a lower frequency. In functional assays, we observed that knockdown of CDH10 promoted cell proliferation, soft-agar colony formation, cell migration and cell invasion, and overexpression of CDH10 inhibited cell proliferation. This mutational landscape of lung SQCC in Chinese patients improves our current understanding of lung carcinogenesis, early diagnosis and personalized therapy